Design of Clinical Research and its Practical Approach -- Advanced Design of Experiment Approach to Clinical and Medical Research -- Random Forest and Concept of Decision Tree Model -- Application of Machine Learning in Medical Research -- Statistical Genetic and its Application in Drug Trail -- Statistical Implications for Estimation of Genetic Traits in Human Vaccine Trail -- Statistical Implications and its Practical Approach to Research Methodology -- Statistical Models Approach to Life Threatened Diseases -- Meta Analysis in Clinical and Life Science Research -- Pharmokinitic and Statistical Modelling -- Imputation Methods Approach to Clinical and Life Science Research Data Sets -- Ethical Perspective of Medical Research.

Recent Statistical techniques are one of the basal evidence for clinical research, a pivotal in handling new clinical research and in evaluating and applying prior research. This book explores various choices of statistical tools and mechanisms, analyses of the associations among different clinical attributes. It uses advanced statistical methods to describe real clinical data sets, when the clinical processes being examined are still in the process. This book also discusses distinct methods for building predictive and probability distribution models in clinical situations and ways to assess the stability of these models and other quantitative conclusions drawn by realistic experimental data sets. Design of experiments and recent posthoc tests have been used in comparing treatment effects and precision of the experimentation. This book also facilitates clinicians towards understanding statistics and enabling them to follow and evaluate the real empirical studies (formulation of randomized control trial) that pledge insight evidence base for clinical practices. This book will be a useful resource for clinicians, postgraduates scholars in medicines, clinical research beginners and academicians to nurture high-level statistical tools with extensive scope.